Visualization of large data sets using MDS combined with LVQ

A common task in data mining is the visualization of multivariate objects using various methods, allowing human observers to perceive subtle inter-relations in the dataset. Multidimensional scaling (MDS) is a well known technique used for this purpose, but it due to its computational complexity there are limitations on the number of objects that can be displayed. Combining MDS with a clustering method as Learning Vector Quantization allows to obtain displays of large databases that preserve both high accuracy of clustering methods and good visualization properties.